LunaPrompts / Assessment templates ASSESSMENT TEMPLATES
Start with the work. Build a better assessment. Practical tasks, scoring rubrics, and follow-up questions for hiring AI engineers. Choose a workflow, adapt the brief, and agree what evidence your team needs.
Choose what you need to evaluate. 01 / AGENT ENGINEERING An agent that completes the happy path is only part of the job. Test what it does when a tool fails, context changes, or an action needs approval.
Practical task · weighted rubric · interview follow-ups
Open the brief ↗ 02 / SYSTEM DESIGN A useful architecture explains the requirements, the tradeoffs, and what happens when something breaks.
Practical task · weighted rubric · interview follow-ups
Open the brief ↗ 03 / AI ENGINEERING A working demo is the start of the conversation. See how candidates evaluate it, handle failure, and defend their decisions.
Practical task · weighted rubric · interview follow-ups
Open the brief ↗ 04 / RETRIEVAL & EVALUATION Evaluate retrieval and answer quality separately. A fluent answer should not hide a poor retrieval pipeline.
Practical task · weighted rubric · interview follow-ups
Open the brief ↗ 05 / AI-ASSISTED DEVELOPMENT Allow the tools the role needs. Evaluate the candidate’s review, debugging, and judgment alongside the code they deliver.
Practical task · weighted rubric · interview follow-ups
Open the brief ↗ 06 / ASSESSMENT INTEGRITY An integrity signal is a reason to investigate. Combine session evidence with the candidate’s work and their explanation before deciding.
Internal pilot template · environment and review checks
Open the brief ↗ Which template fits your role? Choose by the work, not just the job title What the person will do Start here Evidence to examine Ship a complete AI feature AI engineer assessment Correctness, evaluation cases, failure handling, and tradeoffs. Build agents that take actions AI agent assessment Tool contracts, permission boundaries, retries, and stopping rules. Find and ground answers in documents RAG assessment Retrieval quality, citation support, abstention, and version handling. Develop with coding assistants AI-assisted coding assessment Patch correctness, regression tests, and review of generated changes. Own architecture and technical tradeoffs System design assessment Requirements, data boundaries, operations, and capacity assumptions.
Evaluating the assessment process itself? Use the integrity pilot brief to test configured environments with consenting internal testers.
What makes a useful hiring assessment? Give candidates a task connected to the role, make the allowed tools explicit, collect the work, and ask them to explain their choices. Review the evidence against criteria agreed in advance. These templates provide starting points; calibrate them for your role and candidate population.
For implementation examples, explore the Amber hiring case study and JupiterBrains hiring case study . Reported customer outcomes are separate from the illustrative exercises in this library.
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Start with the role you’re hiring for. Bring a job description, a few must-have skills, and your hiring timeline. We’ll help you shape the evaluation.
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